Evidence map›Paper›PMID 24146757›Full record

ArticlePloS one2013

SIDD: a semantically integrated database towards a global view of human disease.

Liang Cheng, Guohua Wang, Jie Li, Tianjiao Zhang, Peigang Xu, Yadong Wang

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Computational Methods for Identifying Similar Diseases.Molecular therapy. Nucleic acids · 2019
    Review
  5. DRUM: Inference of Disease-Associated mFrontiers in genetics · 2019
    Article
  6. Article
  7. Article
  8. Article
  9. Article
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  12. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Liang ChengCenter for Bioinformatics, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, China.
Guohua Wang
Jie Li
Tianjiao Zhang
Peigang Xu
Yadong Wang

Funding

Alcohol dependence and brain endocannabinoid functionR01AA020404 · NIAAA · SCRIPPS RESEARCH INSTITUTE, THE · PI MARTIN-FARDON, REMI · 2011 to 2015
$2.2M
NIAAA NIH HHS R01 AA020404
6 · The paper itself

Abstract

backgroundA number of databases have been developed to collect disease-related molecular, phenotypic and environmental features (DR-MPEs), such as genes, non-coding RNAs, genetic variations, drugs, phenotypes and environmental factors. However, each of current databases focused on only one or two DR-MPEs. There is an urgent demand to develop an integrated database, which can establish semantic associations among disease-related databases and link them to provide a global view of human disease at the biological level. This database, once developed, will facilitate researchers to query various DR-MPEs through disease, and investigate disease mechanisms from different types of data. METHODOLOGY: To establish an integrated disease-associated database, disease vocabularies used in different databases are mapped to Disease Ontology (DO) through semantic match. 4,284 and 4,186 disease terms from Medical Subject Headings (MeSH) and Online Mendelian Inheritance in Man (OMIM) respectively are mapped to DO. Then, the relationships between DR-MPEs and diseases are extracted and merged from different source databases for reducing the data redundancy.

conclusionsA semantically integrated disease-associated database (SIDD) is developed, which integrates 18 disease-associated databases, for researchers to browse multiple types of DR-MPEs in a view. A web interface allows easy navigation for querying information through browsing a disease ontology tree or searching a disease term. Furthermore, a network visualization tool using Cytoscape Web plugin has been implemented in SIDD. It enhances the SIDD usage when viewing the relationships between diseases and DR-MPEs. The current version of SIDD (Jul 2013) documents 4,465,131 entries relating to 139,365 DR-MPEs, and to 3,824 human diseases. The database can be freely accessed from: http://mlg.hit.edu.cn/SIDD.

Indexed as

Computational BiologyDatabases, FactualSoftwareDatabases, BibliographicDiseaseHumansInternetMedical Subject Headings

Identifiers

PMID24146757
PMCPMC3795748

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.